A Bayesian wavelet packet denoising criterion for mechanical signal with non-Gaussian characteristic

Yue, Guodong; Cui, Xiushi; Zou, Yuanyuan; Bai, Xiaotian; Wu, Yuhou; Shi, Huaitao

doi:10.1016/j.measurement.2019.02.066

Cited by 29 publications

(21 citation statements)

References 19 publications

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“…According to the research results, this paper sets the search range of k to [2,15], and the step size is 1; the penalty factor α is set to 2000.…”

Section: Parameter Optimization Based On Permutationmentioning

confidence: 99%

“…VMD decomposes the signal into k IMF components. The effective components are screened by the method in Section 2.2.2, and the reconstructed signal s k ðtÞ is obtained when the number of decomposition layers is k. The search range of k is [2,15]. Therefore, 14 reconstructed signals can be obtained.…”

Section: Parameter Optimization Based On Permutationmentioning

confidence: 99%

“…Similar to the process of optimizing k in Section 2.2.3. Firstly, set the search range of k as [2,15], and the step size is 1; the penalty factor α is set to 2000. Then, the signal is decomposed by VMD.…”

Section: Parameter Optimization Based On Kurtosismentioning

confidence: 99%

“…According to the method in Section 2.2, when k is 5, IMFs with R ux ≥ 0:3 are selected to obtain the reconstructed signal. Accordingly, 14 reconstructed signals are obtained after the search is completed in the range of [2,15]. Then, the permutation entropy of each reconstructed signal is calculated, and the results are shown in Figure 11.…”

Section: Inflection Point Extraction Of the Original Signalmentioning

confidence: 99%

“…Compared with the filter-based method, the wavelet threshold method can obtain a better noise reduction effect [14]. However, the pressure signal and noise in the pipeline are nonlinear and nonstationary signals, and it is difficult to select the appropriate wavelet type and threshold [15]. Empirical mode decomposition (EMD) can decompose the signal adaptively, but it lacks rigorous mathematical derivation.…”

Section: Introductionmentioning

confidence: 99%

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Application of VMD in Pipeline Leak Detection Based on Negative Pressure Wave

2021

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Leakage problems are common in the water supply pipeline system, which will threaten the health of residents and cause economic losses. Negative pressure wave (NPW) technology calculates the time difference through the inflection point to locate the leak. However, due to the nonlinear and nonstationary characteristics of the pressure signal, it is difficult to obtain an accurate inflection point of the NPW by the traditional method. Therefore, the advantages of applying variational mode decomposition (VMD) in NPW technology are explored. Firstly, the correlation coefficient and permutation entropy (PE) are used for effective intrinsic mode function (IMF) component selection and parameter optimization. Thus, an adaptive denoising method based on VMD (AD-VMD) is presented. Then, to effectively separate the detail features of the NPW, a novel inflection point extraction method based on VMD (IPE-VMD) is proposed. Simulation and experimental results show that AD-VMD can effectively suppress noise interference and conserve the mutation characteristic of the leakage. IPE-VMD can obtain a distinct maximum peak at the inflection point and has good robustness to noise interference. This method can calculate the time difference precisely and stably. In addition, the accuracy of the leak location is verified. The average relative positioning error is 5.13%.

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“…According to the research results, this paper sets the search range of k to [2,15], and the step size is 1; the penalty factor α is set to 2000.…”

Section: Parameter Optimization Based On Permutationmentioning

confidence: 99%

Section: Parameter Optimization Based On Permutationmentioning

confidence: 99%

Section: Parameter Optimization Based On Kurtosismentioning

confidence: 99%

Section: Inflection Point Extraction Of the Original Signalmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Application of VMD in Pipeline Leak Detection Based on Negative Pressure Wave

2021

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Walking motion real-time detection method based on walking stick, IoT, COPOD and improved LightGBM

et al. 2022

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Real-time walking behavior monitoring is essential in ensuring safety and improving people's physical conditions with mobility difficulties. In this paper, a real-time walking motion detection system based on the intelligent walking stick, mobile phone and multi-label imbalance classification method combining focal loss and LightGBM (MFGBoost) is proposed. The Internet of Things (IoT) technology is utilized for communicating between the walking stick and mobile phone. The new MFGBoost is embedded into the Raspberry Pi to classify human motions. MFGBoost is scalable, and other boosting models, such as XGBoost, could also be used as its base classifier. An improved derivation method of the multi-classification focal loss function is proposed in this paper, which is the key to the combination of multi-classification focal loss and Boosting algorithms. We propose a novel denoise method based on window matrix and COPOD algorithm (W-OD). The window matrix is designed to extract data features and smooth noise, and COPOD could output the noise level of the model. A weighted loss function is designed to adjust the model's attention to different samples based on the W-OD algorithm. We evaluate the latest classification model from multiple perspectives on multiple benchmark datasets and demonstrate that MFGBoost and W-OD-MFGBoost could improve classification performance and decision-making efficiency. Experiments conducted on human motion datasets show that W-OD-MFGBoost could achieve more than 97 percent classification accuracy.

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Unknown fault diagnosis of planetary gearbox based on optimal rank nonnegative matrix factorization and improved stochastic resonance of bistable system

Yang

Cao

2022

Nonlinear Dyn

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A Bayesian wavelet packet denoising criterion for mechanical signal with non-Gaussian characteristic

Cited by 29 publications

References 19 publications

Application of VMD in Pipeline Leak Detection Based on Negative Pressure Wave

Application of VMD in Pipeline Leak Detection Based on Negative Pressure Wave

Walking motion real-time detection method based on walking stick, IoT, COPOD and improved LightGBM

Unknown fault diagnosis of planetary gearbox based on optimal rank nonnegative matrix factorization and improved stochastic resonance of bistable system

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